Where can I find the most reliable historical stock data for robust backtesting?
Are you tired of hunting for accurate historical stock data?
With so many sources, conflicting figures, and incomplete records, finding trustworthy data for rigorous backtesting can be frustrating.
At Lenz + Partner, we provide reliable historical data through enterprise-grade global data feeds with direct access to major exchanges such as the NYSE and Nasdaq.
Our feeds include adjusted price series, and volume so traders and analysts can build more realistic backtests and make better market decisions.
Key Takeaways
- Direct access to major exchanges (NYSE, Nasdaq) and broad market coverage across equities and indices.
- High-quality historical stock records — adjusted close, price, and volume — suitable for robust backtesting.
- Datasets that reduce look-ahead bias errors to improve trading strategy accuracy.
- Options for intraday or end-of-day data depending on your trading horizon; suitable for both individual traders and institutional users.
- Request a free sample dataset or coverage table to verify number of tickers, years of history, and data range for your universe.
Why Quality Historical Stock Data Is Essential for Successful Backtesting
Quality historical stock data is the foundation of any reliable backtest.
Poorly maintained or incomplete data produces misleading results, overstates strategy performance, and can introduce execution or look-ahead biases that invalidate conclusions.
At Lenz + Partner, we provide curated datasets designed to minimize these risks so traders and quants can trust their outcomes.
Key Considerations for Choosing Historical Stock Data
Accuracy and Reliability
Choosing the right historical stock data means checking for accuracy, completeness, and consistent adjustments.
Our feeds include adjusted price series (adjusted close and open), and volume so backtests reflect real-world returns after splits and dividends.
A typical offering documents the number of tickers covered, the years of history available, and the date/time range for intraday or end-of-day records.
Completeness and Granularity
Decide whether you need tick, minute, or daily price data — the trading horizon determines the necessary granularity.
For intraday trading you need fine-grained ticks or minute bars; for strategy-level signals, daily prices and volume are often sufficient.
Ensure the dataset contains continuous ticker histories and index membership records, so index-based strategies reference correct constituents over time.
Adjustments
Unadjusted price series can break a backtest: a 2-for-1 split will halve historical prices and falsely signal a drop unless adjusted.
Our datasets apply split and dividend adjustments and tag corporate actions so your backtest engine uses correct, adjusted price and total-return series as a reliable reference for performance calculations.
Coverage, Licensing, and Reference Standards
Evaluate coverage (which markets and indices are included), licensing terms (redistribution, commercial use), and whether the provider follows industry reference standards for timestamps and trading calendars.
Where possible, compare samples against known benchmarks (exchange-provided files or audited datasets) to validate integrity.
Example: How Bad Data Skews Results
Consider a momentum strategy tested on unadjusted daily prices: dividend payments and splits produce artificial jumps that the strategy could misinterpret as tradable signals, inflating returns.
With adjusted price and accurate volume history, the same strategy shows realistic Sharpe ratios and drawdowns, giving a truer picture for trading decisions.
Data Providers for Historical Stock Data
Popular Data Providers
When sourcing historical stock data you’ll find three broad provider tiers: free APIs, freemium aggregators, and enterprise-grade vendors.
Each has trade-offs in coverage, price, and reliability.
Practical guidance: choose free or freemium providers for exploratory analysis, back-of-envelope testing, and news-driven screens; pick paid or enterprise feeds for production trading, large-universe backtests, and when accurate intraday price and volume history or guaranteed coverage of indices is required.
Compare datasets on these criteria: ticker universe size, years of history, intraday vs end-of-day range, whether prices are adjusted (adjusted close), volume completeness, and licensing terms.
Request a sample coverage file to validate tick-level timestamps, trading-calendar alignment, and that reference indices and corporate-action tags are present before committing to a vendor.
How to Get Started
Our data services give you reliable access to historical market records so you can analyze asset performance and refine trading strategies with confidence.
Choose between end-of-day feeds for strategy-level research or intraday feeds when your trading signals require minute or tick granularity.
Each dataset includes adjusted price series, and volume, as a reference for correct performance calculation.
Request a sample to inspect the number of tickers, years of history, and the date/time range for your universe, or ask for a coverage table showing indices and exchange coverage.
We also provide integration support for APIs and data-feed ingestion so teams can move from sample to production faster.
Ready to validate your backtests?
Schedule a demo or download a 30-day sample dataset to compare against your current sources and see how improved coverage and clean, adjusted data reduce false signals and improve decision-making.